Climate change and decadal to centennial-scale periodicities recorded in a late Holocene NE Pacific marine record: Examining the role of solar forcing

We present a decadal-scale late Holocene climate record based on diatoms, biogenic silica, and grain size from a 12-m sediment core (VEC02A04) obtained from Frederick Sound in the Seymour-Belize Inlet Complex of British Columbia, Canada. Sediments are characterized by graded, massive, and laminated intervals. Laminated intervals are most common between c. 2948–2708 cal. yr BP and c. 1992–1727 cal. yr BP. Increased preservation of laminated sediments and diatom assemblage changes at this time suggest that cli- mate became moderately drier and cooler relative to the preceding and succeeding intervals. Spectral and wavelet analyses are used to test for statistically significant periodicities in time series of proxies of primary production (total diatom abundance, biogenic silica) and hydrology (grain size) preserved in the Frederick Sound record. Periodicities of c. 42–53, 60–70, 82–89, 241–243, and 380 yrs are present. Results are com- pared to reconstructed sunspot number data of Solanki et al. (2004) using cross wavelet transform to evalu- ate the role of solar forcing on NE Pacific climate. Significant common power of periodicities between c. 42– 60, 70–89, 241–243, and of 380 yrs occur, suggesting that celestial forcing impacted late Holocene climate at Frederick Sound. Replication of the c. 241–243 yr periodicity in sunspot time series is most pronounced be- tween c. 2900 cal. yr BP and c. 2000 cal. yr BP, broadly correlative to the timing of maximum preservation of laminated sedimentary successions and diatom assemblage changes. High solar activity at the Suess/de Vries band may have been manifested as a prolonged westward shift and/or weakening of the Aleutian Low in the mid-late Holocene, which would have diverted fewer North Pacific storms and resulted in the relatively dry conditions reconstructed for the Seymour-Belize Inlet Complex.

TRACE observations of driven loop oscillations

Aims: On 13 June 1998, the TRACE satellite was fortuitously well placed to observe the effects of a flare-induced EIT wave in the corona, and its subsequent interaction with coronal magnetic loops. In this study, we use these TRACE observations to corroborate previous theoretical work, which determined the response of a coronal loop to a harmonic driver in the context of ideal magnetohydrodynamics, as well as estimate the magnetic field strength and the degree of longitudinal inhomogeneity. Methods: Loop edges are tracked, both spatially and temporally, using wavelet modulus maxima algorithms, with corresponding loop displacements from its quiescent state analysed by fitting scaled sinusoidal functions. The physical parameters of the coronal loop are subsequently determined using seismological techniques. Results: The studied coronal loop is found to oscillate with two distinct periods, 501 ± 5 s and 274 ± 7 s, which could be interpreted as belonging to the fundamental kink mode and first harmonic, or could reflect the stage of an overdriven loop. Additional scenarios for explaining the two periods are listed, each resulting in a different value of the magnetic field and the intrinsic and sub-resolution properties of the coronal loop. When assuming the periods belong to the fundamental kink mode and its first harmonic, we obtain a magnetic field strength inside the oscillating coronal loop of 2.0 ± 0.7 G. In contrast, interpreting the oscillations as a combination of the loop's natural kink frequency and a harmonic EIT wave provides a magnetic field strength of 5.8 ± 1.5 G. Using the ratio of the two periods, we find that the gravitational scale height in the loop is 73 ± 3 Mm. Conclusions: We show that the observation of two distinct periods in a coronal loop does not necessarily lead to a unique conclusion. Multiple plausible scenarios exist, suggesting that both the derived strength of the magnetic field and the sub-resolution properties of the coronal loop depend entirely on which interpretation is chosen. The interpretation of the observations in terms of a combination of the natural kink mode of the coronal loop, driven by a harmonic EIT wave seems to result in values of the magnetic field consistent with previous findings. Other interpretations, which are realistic, such as kink fundamental mode/first harmonic and the oscillations of two sub-resolution threads result in magnetic field strengths that are below the average values found before.

Low-power DWT-based quasi-averaging algorithm and architecture for epileptic seizure detection

In this paper, we have developed a low-complexity algorithm for epileptic seizure detection with a high degree of accuracy. The algorithm has been designed to be feasibly implementable as battery-powered low-power implantable epileptic seizure detection system or epilepsy prosthesis. This is achieved by utilizing design optimization techniques at different levels of abstraction. Particularly, user-specific critical parameters are identified at the algorithmic level and are explicitly used along with multiplier-less implementations at the architecture level. The system has been tested on neural data obtained from in-vivo animal recordings and has been implemented in 90nm bulk-Si technology. The results show up to 90 % savings in power as compared to prevalent wavelet based seizure detection technique while achieving 97% average detection rate. Copyright 2010 ACM.

Using Brain Data for Sentiment Analysis

We present the results of exploratory experiments using lexical valence extracted from brain using electroencephalography (EEG) for sentiment analysis. We selected 78 English words (36 for training and 42 for testing), presented as stimuli to 3 English native speakers. EEG signals were recorded from the subjects while they performed a mental imaging task for each word stimulus. Wavelet decomposition was employed to extract EEG features from the time-frequency domain. The extracted features were used as inputs to a sparse multinomial logistic regression (SMLR) classifier for valence classification, after univariate ANOVA feature selection. After mapping EEG signals to sentiment valences, we exploited the lexical polarity extracted from brain data for the prediction of the valence of 12 sentences taken from the SemEval-2007 shared task, and compared it against existing lexical resources.

Coupled Effects of a Perturbation in a Complex Structure Observed with SDO/AIA, SDO/HMI and ROSA/HARDcam

We study properties of intensity fluctuations in NOAA Active Region 11250 observed on 13 July 2011 starting at UT 13:32. Included are data obtained in the EUV bands of the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory (SDO/AIA) as well as nearly simultaneous observations of the chromosphere made, at much higher spatial and temporal resolution, with the Rapid Oscillations in the Solar Atmosphere (ROSA) and Hydrogen-Alpha Rapid Dynamics camera (HARDcam) systems at the Dunn Solar Telescope. A complex structure seen in both the ROSA/HARDcam and SDO data sets comprises a system of loops extending outward from near the boundary of the leading sunspot umbra. It is visible in the ROSA Ca II K and HARDcam Hα images, as well as the SDO 304 Å, 171 Å and 193 Å channels, and it thus couples the chromosphere, transition region and corona. In the ground-based images the loop structure is 4.1 Mm long. Some 17.5 Mm, can be traced in the SDO/AIA data. The chromospheric emissions observed by ROSA and HARDcam appear to occupy the inner, and apparently cooler and lower, quarter of the loop. We compare the intensity fluctuations of two points within the structure. From alignment with SDO/HMI images we identify a point "A" near the loop structure, which sits directly above a bipolar magnetic feature in the photosphere. Point "B" is characteristic of locations within the loops that are visible in both the ROSA/HARDcam and the SDO/AIA data. The intensity traces for point A are quiet during the first part of the data string. At time ~ 19 min they suddenly begin a series of impulsive brightenings. In the 171 Å and 193 Å coronal lines the brightenings are localized impulses in time, but in the transition region line at 304 Å they are more extended in time. The intensity traces in the 304 Å line for point B shows a quasi-periodic signal that changes properties at about 19 min. The wavelet power spectra are characterized by two periodicities. A 6.7 min period extends from the beginning of the series until about 25 minutes, and another signal with period ~3 min starts at about 20 min. The 193 Å power spectrum has a characteristic period of 5 min, before the 20 min transition and a 2.5 min periodicity afterward. In the case of HARDcam Hα data a localized 4 min periodicity can be found until about 7 min, followed by a quiet regime. After ~20 min a 2.3 min periodicity appears. Interestingly a coronal loop visible in the 94 Å line that is centrally located in the AR, running from the leading umbra to the following polarity, at about time 20 min undergoes a strong brightening beginning at the same moment all along 15 Mm of its length. The fact that these different signals all experience a clear-cut change at time about 20 min suggests an underlying organizing mechanism. Given that point A has a direct connection to the photospheric magnetic bipole, we conjecture that the whole extended structure is connected in a complex manner to the underlying magnetic field. The periodicities in these features may favor the wave nature rather than upflows and interpretations will be discussed.

Rapid Oscillations in the Solar Atmosphere: Spectra and Physical Effects

High-frequency fluctuations are observed with the Rapid Oscillations in the Solar Atmosphere (ROSA) instrument (Jess et al. 2010, Solar Phys, 261, 363) at the Dunn Solar Telescope. This can produce simultaneous observations in up to six channels, at different heights in the photosphere and chromosphere, at an unprecedentedly high cadence of 0.5 seconds, and at a spatial resolution of 100 km after photometrically correct speckle reconstruction. Here we concentrate on observations at two levels. The first is in the G-band of the CH radical at 4305.5Å, bandpass 9.2Å, with height of formation z <250 km at a cadence of 0.525 sec corresponding to Nyquist frequency 950 mHz. The second is in the Ca II K-line core at 3933.7Å, bandpass 1.0Å, with height of formation z <1300 km, and cadence 4.2 sec giving Nyquist frequency 120 mHz. The data span 53 min, and the maximum field of view is 45 Mm. The data were taken on 28 May 2009 in internetwork and network near disk center. Using both Fourier and Morlet wavelet methods we find evidence in the G-band spectra for intensity fluctuations above noise out to frequencies f >> 100 mHz. The K-line signal is noisier and is seen only for f <50 mHz. With wavelet techniques we find that G-band spectral power with 20 <f <100 mHz is clearly concentrated in the intergranular lanes and especially at the locations of magnetic elements indicated by G-band bright points. This wavelet power is highly intermittent in time. By cross-correlating the data we find that pulses of high-frequency G-band power in the photosphere tend to be followed by increases in K-line emission in the chromosphere with a time lag of about 2 min.

Wave Damping Observed in Upwardly Propagating Sausage-Mode Oscillations Contained within a Magnetic Pore

We present observational evidence of compressible MHD wave modes propagating from the solar photosphere through to the base of the transition region in a solar magnetic pore. High cadence images were obtained simultaneously across four wavelength bands using the Dunn Solar Telescope. Employing Fourier and wavelet techniques, sausage-mode oscillations displaying significant power were detected in both intensity and area fluctuations. The intensity and area fluctuations exhibit a range of periods from 181 to 412 s, with an average period∼290 s, consistent with the global p-mode spectrum. Intensity and area oscillations present in adjacent band passes were found to be out of phase with one another, displaying phase angles of 6.°12, 5.°82,and 15.°97 between the 4170 Å continuum–G-band,G-band–Na i D1, and Na i D1–Ca ii K heights, respectively, reiterating the presence of upwardly propagating sausage-mode waves. A phase relationship of ∼0° between same-bandpass emission and area perturbations of the pore best categorizes the waves as belonging to the “slow” regime of a dispersion diagram. Theoretical calculations reveal that the waves are surface modes, with initial photospheric energies in excess of 35,000 Wm‑2. The wave energetics indicate a substantial decrease in energy with atmospheric height, confirming that magnetic pores are able to transport waves that exhibit appreciable energy damping, which may release considerable energy into the local chromospheric plasma.

Ultrasound entropy may be a new non-invasive measure of pre-clinical vascular damage in young hypertensive patients

Background: The identification of pre-clinical microvascular damage in hypertension by non-invasive techniques has proved frustrating for clinicians. This proof of concept study investigated whether entropy, a novel summary measure for characterizing blood velocity waveforms, is altered in participants with hypertension and may therefore be useful in risk stratification.

Methods: Doppler ultrasound waveforms were obtained from the carotid and retrobulbar circulation in 42 participants with uncomplicated grade 1 hypertension (mean systolic/diastolic blood pressure (BP) 142/92 mmHg), and 26 healthy controls (mean systolic/diastolic BP 116/69 mmHg). Mean wavelet entropy was derived from flow-velocity data and compared with traditional haemodynamic measures of microvascular function, namely the resistive and pulsatility indices.

Results: Entropy, was significantly higher in control participants in the central retinal artery (CRA) (differential mean 0.11 (standard error 0.05 cms(-1)), CI 0.009 to 0.219, p 0.017) and ophthalmic artery (0.12 (0.05), CI 0.004 to 0.215, p 0.04). In comparison, the resistive index (0.12 (0.05), CI 0.005 to 0.226, p 0.029) and pulsatility index (0.96 (0.38), CI 0.19 to 1.72, p 0.015) showed significant differences between groups in the CRA alone. Regression analysis indicated that entropy was significantly influenced by age and systolic blood pressure (r values 0.4-0.6). None of the measures were significantly altered in the larger conduit vessel.

Conclusion: This is the first application of entropy to human blood velocity waveform analysis and shows that this new technique has the ability to discriminate health from early hypertensive disease, thereby promoting the early identification of cardiovascular disease in a young hypertensive population.

Forward and backward least angle regression for nonlinear system identification

A forward and backward least angle regression (LAR) algorithm is proposed to construct the nonlinear autoregressive model with exogenous inputs (NARX) that is widely used to describe a large class of nonlinear dynamic systems. The main objective of this paper is to improve model sparsity and generalization performance of the original forward LAR algorithm. This is achieved by introducing a replacement scheme using an additional backward LAR stage. The backward stage replaces insignificant model terms selected by forward LAR with more significant ones, leading to an improved model in terms of the model compactness and performance. A numerical example to construct four types of NARX models, namely polynomials, radial basis function (RBF) networks, neuro fuzzy and wavelet networks, is presented to illustrate the effectiveness of the proposed technique in comparison with some popular methods.

Material Identification of Loose Particles in Sealed Electronic Devices Using PCA and SVM

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, these features are usually overlapped and redundant, resulting in unsatisfactory material identification accuracy. The main objective of this paper is to improve the accuracy of material identification. First, the principal component analysis (PCA) is employed to reselect the nine features extracted from time and frequency domains, leading to six less correlated principal components. And then the reselected principal components are used for material identification using a support vector machine (SVM). Finally, the experimental results show that this new method can effectively distinguish the type of materials including wire, aluminum and tin particles.

Supervised Aggregative Feature Extraction for Big Data Time Series Regression

In many applications, and especially those where batch processes are involved, a target scalar output of interest is often dependent on one or more time series of data. With the exponential growth in data logging in modern industries such time series are increasingly available for statistical modeling in soft sensing applications. In order to exploit time series data for predictive modelling, it is necessary to summarise the information they contain as a set of features to use as model regressors. Typically this is done in an unsupervised fashion using simple techniques such as computing statistical moments, principal components or wavelet decompositions, often leading to significant information loss and hence suboptimal predictive models. In this paper, a functional learning paradigm is exploited in a supervised fashion to derive continuous, smooth estimates of time series data (yielding aggregated local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The proposed Supervised Aggregative Feature Extraction (SAFE) methodology can be extended to support nonlinear predictive models by embedding the functional learning framework in a Reproducing Kernel Hilbert Spaces setting. SAFE has a number of attractive features including closed form solution and the ability to explicitly incorporate first and second order derivative information. Using simulation studies and a practical semiconductor manufacturing case study we highlight the strengths of the new methodology with respect to standard unsupervised feature extraction approaches.

Essays on energy derivatives pricing and financial risk management

This thesis consists of an introductory chapter (essay I) and five more empirical essays on electricity markets and CO2 spot price behaviour, derivatives pricing analysis and hedging. Essay I presents the structure of the thesis and electricity markets functioning and characteristics, as well as the type of products traded, to be analyzed on the following essays. In the second essay we conduct an empirical study on co-movements in electricity markets resorting to wavelet analysis, discussing long-term dynamics and markets integration. Essay three is about hedging performance and multiscale relationships in the German electricity spot and futures markets, also using wavelet analysis. We concentrate the investigation on the relationship between coherence evolution and hedge ratio analysis, on a time-frequency-scale approach, between spot and futures which conditions the effectiveness of the hedging strategy. Essays four, five and six are interrelated between them and with the other two previous essays given the nature of the commodity analyzed, CO2 emission allowances, traded in electricity markets. Relationships between electricity prices, primary energy fuel prices and carbon dioxide permits are analyzed on essay four. The efficiency of the European market for allowances is examined taking into account markets heterogeneity. Essay five analyzes stylized statistical properties of the recent traded asset CO2 emission allowances, for spot and futures returns, examining also the relation linking convenience yield and risk premium, for the German European Energy Exchange (EEX) between October 2005 and October 2009. The study was conducted through empirical estimations of CO2 allowances risk premium, convenience yield, and their relation. Future prices from an ex-post perspective are examined to show evidence for significant negative risk premium, or else a positive forward premium. Finally, essay six analyzes emission allowances futures hedging effectiveness, providing evidence for utility gains increases with investor’s preference over risk. Deregulation of electricity markets has led to higher uncertainty in electricity prices and by presenting these essays we try to shed new lights about structuring, pricing and hedging in this type of markets.

Étude numérique des phénomènes transitoires dans une turbine axiale de type hélice durant l’emballement

Ce mémoire présente l’étude numérique d’un emballement de turbine hydraulique axiale à échelle modèle. Cet état transitoire est simulé du point de meilleur rendement jusqu’à l’atteinte de 95% de la vitesse d’emballement. Pour ce faire, une méthodologie numérique est développée à l’aide du logiciel commercial ANSYS CFX en utilisant une approche "Unsteady Reynolds Averaged Navier-Stokes" avec modèle de turbulence k-ε. Cette méthodologie numérique a été validée grâce à des mesures expérimentales de pression acquises en situation d’emballement sur les aubes d’une roue de turbine axiale étudiée au Laboratoire de Machines Hydrauliques de l’Université Laval. La validation des simulations numériques a été réalisée grâce à des comparaisons dans les domaines temporel et fréquentiel entre les pressions mesurées expérimentalement et calculées numériquement. Les analyses fréquentielles en transitoire ont été effectuées à l’aide de transformées en ondelettes afin de représenter l’évolution temporelle du spectre de fréquence. Des analyses qualitatives de phénomènes hydrauliques prenant place dans la turbine sont aussi présentées. Les analyses effectuées ont permis de confirmer le développement d’un tourbillon en précession par rapport à la roue dans l’aspirateur provocant les fluctuations de pression dominantes à des fréquences subsynchrones. La comparaison entre les données expérimentales et numériques a permis de valider une stratégie de simulation transitoire et d’en définir les limites en vue de prochaines simulations d’emballement. Des tests supplémentaires sont suggérés pour améliorer la précision ou le niveau de confiance de la méthode.

Dual studies on autonomic function and cerebral autoregulation in ischemic stroke patients

Tese de mestrado, Neurociências, Faculdade de Medicina, Universidade de Lisboa, 2015

Grid structure impact in sparse point representation of derivatives

In the Sparse Point Representation (SPR) method the principle is to retain the function data indicated by significant interpolatory wavelet coefficients, which are defined as interpolation errors by means of an interpolating subdivision scheme. Typically, a SPR grid is coarse in smooth regions, and refined close to irregularities. Furthermore, the computation of partial derivatives of a function from the information of its SPR content is performed in two steps. The first one is a refinement procedure to extend the SPR by the inclusion of new interpolated point values in a security zone. Then, for points in the refined grid, such derivatives are approximated by uniform finite differences, using a step size proportional to each point local scale. If required neighboring stencils are not present in the grid, the corresponding missing point values are approximated from coarser scales using the interpolating subdivision scheme. Using the cubic interpolation subdivision scheme, we demonstrate that such adaptive finite differences can be formulated in terms of a collocation scheme based on the wavelet expansion associated to the SPR. For this purpose, we prove some results concerning the local behavior of such wavelet reconstruction operators, which stand for SPR grids having appropriate structures. This statement implies that the adaptive finite difference scheme and the one using the step size of the finest level produce the same result at SPR grid points. Consequently, in addition to the refinement strategy, our analysis indicates that some care must be taken concerning the grid structure, in order to keep the truncation error under a certain accuracy limit. Illustrating results are presented for 2D Maxwell's equation numerical solutions.